1. Python: An Overview

2. What Is Python?

Created in 1990 by Guido van Rossum

About the origin of Python, Van Rossum wrote in 1996:

Over six years ago, in December 1989, I was looking for a "hobby" programming project that would keep me occupied during the week around Christmas. My office would be closed, but I had a home computer, and not much else on my hands. I decided to write an interpreter for the new scripting language I had been thinking about lately: a descendant of ABC that would appeal to Unix/C hackers. I chose Python as a working title for the project, being in a slightly irreverent mood (and a big fan of Monty Python's Flying Circus).

3. Is Python A Scripting Language?

Usually thought of as one

But this is mainly a marketing issue

• People think of scripting languages as being easy to learn, and useful.

But Python is a well worked out coherent dynamic programming language

• And there is no reason not to use it for a wide range of applications.

4. Design Philosophy >>> import this The Zen of Python, by Tim Peters Beautiful is better than ugly. Explicit is better than implicit. Simple is better than complex. Complex is better than complicated. Flat is better than nested. Sparse is better than dense. Readability counts. Special cases aren't special enough to break the rules. Although practicality beats purity. Errors should never pass silently. Unless explicitly silenced. In the face of ambiguity, refuse the temptation to guess. There should be one-- and preferably only one --obvious way to do it. Although that way may not be obvious at first unless you're Dutch. Now is better than never. Although never is often better than *right* now. If the implementation is hard to explain, it's a bad idea. If the implementation is easy to explain, it may be a good idea. Namespaces are one honking great idea -- let's do more of those! 5. Why Python?

Designed to be easy to learn and master

• Clean, clear syntax

• Very few keywords

Highly portable

• Runs almost anywhere - high end servers and workstations, down to windows CE

• Uses machine independent byte-codes

Extensible

• Designed to be extensible using C/C++, allowing access to many external libraries

6. Most obvious and notorious features

Clean syntax plus high-level data types

• Leads to fast coding (First language in many universities abroad!)

Uses white-space to delimit blocks

• Humans generally do, so why not the language?

• Try it, you will end up liking it

Variables do not need declaration

• Although not a type-less language

7. Productivity!

Reduced development time

• • code is 2-10x shorter than C, C++, Java

Improved program maintenance

• • code is extremely readable

Less training

• • language is very easy to learn

8. What is it used for?

• rapid prototyping

• web scripting

• throw-away, ad hoc programming

• steering scientific applications

• extension language

• XML processing

• database applications

• GUI applications

• A Glue Language

9. PYTHON COMPARED TO OTHER LANGUAGES 10. Python vs. Perl

• Easier to learn

• • important for occasional users

• More readable code

• • improved code maintenance

• Fewer magical side effects

• More safety guarantees

• Better Java integration

• Less Unix bias

11. Python vs. Tcl

• Real datatypes, object-orientation

• More differentiated syntax

• Much faster (even than Tcl 8.x)

• Less need for C extensions

• C extensions dont redefine syntax

• • hence fewer extension conflicts

• Better Java integration

• Python uses Tk as de-facto GUI std

12. Python vs. Java

• Code 5-10 times more concise

• Dynamic typing

• Much quicker development

• • no compilation phase

• • less typing

• Yes, it runs slower

• • but development is so much faster!

Use Python with Java: Jython!

13. Python Basics 14. Python Programs

Python programs and modules are written as text files with traditionally a.pyextension

Each Python module has its own discrete namespace

Name space within a Python module is a global one.

15. Python Programs

Python modules and programs are differentiated only by the way they are called

• .py files executed directly are programs (often referred to as scripts)

• .py files referenced via theimportstatement are modules

16. Python Programs

Thus, the same .py file can be a program/script, or a module

This feature is often used to provide regression tests for modules

• When module is executed as a program, the regression test is executed

• When module is imported, test functionality is not executed

17. Variables and Types(1 of 3)

Variables need no declaration

>>> a=1 >>>

As a variable assignment is a statement, there is no printed result

>>> a 1

Variable name alone is an expression, so the result is printed

18. Variables and Types(2 of 3)

Variables must be created before they can be used

>>> b Traceback (innermost last): File "", line 1, in ? NameError: b >>>

Python uses exceptions - more detail later

19. Variables and Types(3 of 3)

Objects always have a type

>>> a = 1 >>> type(a) >>> a = "Hello" >>> type(a) >>> type(1.0)

20. Assignment versus Equality Testing

Assignment performed with single =

Equality testing done with double = (==)

• Sensible type promotions are defined

• Identity tested withisoperator.

>>> 1==1 1 >>> 1.0==1 1 >>> "1"==1 0

21. Simple Data Types

Strings

• May hold any data, including embedded NULLs

• Declared using either single, double, or triple quotes

• >>> s = "Hi there" >>> s 'Hi there' >>> s = "Embedded 'quote'" >>> s "Embedded 'quote'"

22. Simple Data Types

• Triple quotes useful for multi-line strings

• >>> s = """ a long ... string with "quotes" or anything else""" >>> s ' a long12string with "quotes" or anything else'>>> len(s) 45

23. Simple Data Types

Integer objects implemented using C longs

• Like C, integer division returns the floor

• >>> 5/2 2

Float types implemented using C doubles

• No point in having single precision since execution overhead is large anyway

24. Simple Data Types

Long Integers have unlimited size

• Limited only by available memory

• >>> long = 1L >> long ** 5 2135987035920910082395021706169552114602704522356652769947041607822219725780640550022962086936576L

25. High Level Data Types

Lists hold a sequence of items

• May hold any object

• Declared using square brackets

>>> l = []# An empty list >>> l.append(1) >>> l.append("Hi there") >>> len(l) 2

26. High Level Data Types

>>> l [1, 'Hi there'] >>> >>> l = ["Hi there", 1, 2] >>> l ['Hi there', 1, 2] >>> l.sort() >>> l [1, 2, 'Hi there']

27. High Level Data Types

Tuples are similar to lists

• Sequence of items

• Key difference is they are immutable

• Often used in place of simple structures

Automatic unpacking

>>> point = 2,3 >>> x, y = point >>> x 2

28. High Level Data Types

Tuples are particularly useful to return multiple values from a function

>>> x, y = GetPoint()

As Python has no concept of byref parameters, this technique is used widely

29. High Level Data Types

Dictionaries hold key-value pairs

• Often called maps or hashes.Implemented using hash-tables

• Keys may be any immutable object, values may be any object

• Declared using braces

>>> d={} >>> d[0] = "Hi there" >>> d["foo"] = 1

30. High Level Data Types

Dictionaries (cont.)

>>> len(d) 2 >>> d[0] 'Hi there' >>> d = {0 : "Hi there", 1 : "Hello"} >>> len(d) 2

31. Blocks

Blocks are delimited by indentation

• Colon used to start a block

• Tabs or spaces may be used

• Maxing tabs and spaces works, but is discouraged

>>> if 1: ...print "True" ...True >>>

32. Blocks

Many hate this when they first see it

• Most Python programmers come to love it

Humans use indentation when reading code to determine block structure

• Ever been bitten by the C code?:

if (1) printf("True"); CallSomething();

33. Looping

Theforstatement loops over sequences

>>> for ch in "Hello": ...print ch ...H e l l o >>>

34. Looping

Built-in functionrange()used to build sequences of integers

>>> for i in range(3): ...print i ...0 1 2 >>>

35. Looping

whilestatement for more traditional loops

>>> i = 0 >>> while i < 2: ...print i ...i = i + 1 ...0 1 >>>

36. Functions

Functions are defined with thedefstatement:

>>> def foo(bar): ...return bar >>>

This defines a trivial function namedfoothat takes a single parameterbar

37. Functions

A function definition simply places a function object in the namespace

>>> foo >>>

And the function object can obviously be called:

>>> foo(3) 3 >>>

38. Classes

Classes are defined using theclassstatement

>>> class Foo: ...def __init__(self): ...self.member = 1 ...def GetMember(self): ...return self.member ...>>>

39. Classes

A few things are worth pointing out in the previous example:

• The constructor has a special name__init__ , while a destructor (not shown) uses__del__

• Theselfparameter is the instance (ie, thethisin C++).In Python, the self parameter is explicit (c.f. C++, where it is implicit)

• The nameselfis not required - simply a convention

40. Classes

Like functions, a class statement simply adds a class object to the namespace

>>> Foo >>>

Classes are instantiated using call syntax

>>> f=Foo() >>> f.GetMember() 1

41. Modules

Most of Pythons power comes from modules

Modules can be implemented either in Python, or in C/C++

importstatement makes a module available

>>> import string >>> string.join( ["Hi", "there"] ) 'Hi there' >>>

42. Exceptions

Python uses exceptions for errors

• try/exceptblock can handle exceptions

>>> try: ...1/0 ... except ZeroDivisionError: ...print "Eeek" ...Eeek >>>

43. Exceptions

try/finallyblock can guarantee execute of code even in the face of exceptions

>>> try: ...1/0 ... finally: ...print "Doing this anyway" ...Doing this anyway Traceback (innermost last):File "", line 2, in ? ZeroDivisionError: integer division or modulo >>>

44. Threads

Number of ways to implement threads

Highest level interface modelled after Java

>>> class DemoThread(threading.Thread): ...def run(self): ...for i in range(3): ...time.sleep(3) ...print i ...>>> t = DemoThread() >>> t.start() >>> t.join() 0 1

45. Standard Library

Python comes standard with a set of modules, known as the standard library

Incredibly rich and diverse functionality available from the standard library

• All common internet protocols, sockets, CGI, OS services, GUI services (via Tcl/Tk), database, Berkeley style databases, calendar, Python parser, file globbing/searching, debugger, profiler, threading and synchronisation, persistency, etc

46. External library

Many modules are available externally covering almost every piece of functionality you could ever desire

• Imaging, numerical analysis, OS specific functionality, SQL databases, Fortran interfaces, XML, Corba, COM, Win32 API, comedilib, serial, parallel, opengl, opencv, wxpython, gtk, qt, tkinter etc

Way too many to give the list any justice

47. More Information on Python

Comes with extensive documentation, including tutorials and library reference

• Also a number of Python books available

Visitwww.python.orgfor more details

• Can find python tutorial and reference manual